• Journal of Advanced Marine Engineering and Technology
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• v.28 no.8
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• pp.1299-1312
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• 2004

This paper suggests the simple form of a fuzzy PID controller and describes the design principle, tracking performance, stability analysis and changes of parameters of a suggested fuzzy PID controller. A fuzzy PID controller is derived from the design procedure of fuzzy control. It is well known that a fuzzy PID controller has a simple structure of the conventional PID controller but posses its self-tuning control capability and the gains of a fuzzy PID controller become nonlinear functions of the inputs. Nonlinear calculation during fuzzification, defuzzification and the fuzzy inference require more time in computation. To increase the applicability of a fuzzy PID controller to digital computer, a simple form of a fuzzy PID controller is introduced by the backward difference mapping and the analysis of the fuzzy input space. To guarantee the BIBO stability of a suggested fuzzy PID controller, ‘small gain theorem’ which proves the BIBO stability of a fuzzy PI and a fuzzy PD controller is used. After a detailed stability analysis using ‘small gain theorem’, from which a simple and practical method to decide the parameters of a fuzzy PID controller is derived. Through the computer simulations for the linear and nonlinear plants, the performance of a suggested fuzzy PID controller will be assured and the variation of the gains of a fuzzy PID controller will be investigated.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.2
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• pp.325-333
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• 2016

This paper proposes controller design algorithms for a ceramic soldering iron temperature control system, and reports their effectiveness in a control experiment. Because the responses of the ceramic soldering iron temperature to the control input are non-linear and very slow, precise modeling and controller design is difficult. In this study, the temperature characteristics of a ceramic soldering iron are represented by TSK fuzzy models consisting of TSK fuzzy rules. In the fuzzy rules, the premise variable is the control input and the consequences are the transfer functions. The transfer functions in the fuzzy model were obtained from the step input responses. As the responses of the ceramic soldering iron temperature are very slow, it is difficult to obtain the complete step input responses. This paper proposes a genetic algorithm to obtain the transfer functions from an incomplete step input responses, and showed its effectiveness in examples. This paper also reports a fuzzy controller design method from the TSK fuzzy model and examples. The proposed methods were applied to the temperature control experiments of ceramic iron. The TSK fuzzy model consisted of 7 TSK fuzzy rules, and the consequences were PI controllers. The experimental results of the proposed fuzzy PI controller were superior to the linear controller and were as good as in previous studies using a fuzzy PID controller.

• Journal of Power Electronics
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• v.9 no.1
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• pp.109-116
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• 2009

This paper addresses the output control of a utility-connected double-fed induction machine (DFIM) for wind power generation systems (WPGS). DFIM has a back-to-back converter to control outputs of DFIM driven by the wind turbine for WPGS. To supply commercially the power of WPGS to the grid without any problems related to power quality, the real and reactive powers (PQ) at the stator side of DFIM are strictly controlled at the required level, which in this paper is realized with the Fuzzy PI controller based on the field orientation control. For the Sinusoidal Pulse Width Modulation (SPWM) converter connected to the rotor side of DFIG to maintain the controllability of PQ at the state side of DFIM, the DC voltage of the DC link capacitor is also controlled at a certain level with the conventional Proportion-Integral (PI) controller of the real power. In addition, the power quality at the grid connected to the rotor side of DFIM through the back-to-back converter is maintained in a certain level with a PI controller of the reactive power. The controllers for the PQ at the stator side of DFIM, the DC link voltage of the back-to-back inverter and the reactive power at the grid connected to the rotor side of DFIM are designed and simulated in the PSIM program, of which the result verifies the performance of the proposed controllers.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.19 no.8
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• pp.48-55
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• 2005

This paper presents a new speed control scheme of the spindle induction motor(IM) using fuzzy controller(FC) in field weakening region. The implementation of the proposed FC based spindle Induction Motor(IM) is compared to those obtained from the conventional PI controller based drive system. The simulation and experimental results show that the FC is the high performance more than the conventional PI speed controller in the spindle drive systems.

• International Journal of Control, Automation, and Systems
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• v.4 no.2
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• pp.155-164
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• 2006

This paper focuses on a new optimization technique of a fuzzy logic based proportional integral (FLPI) load frequency controller by the multiple tabu search (MTS) algorithm. Conventionally, the membership functions and control rules of fuzzy logic control are obtained by trial and error method or experiences of designers. To overcome this problem, the MTS algorithm is proposed to simultaneously tune proportional integral gains, the membership functions and control rules of a FLPI load frequency controller in order to minimize the frequency deviations of the interconnected power system against load disturbances. The MTS algorithm introduces additional techniques for improvement of the search process such as initialization, adaptive search, multiple searches, crossover and restart process. Simulation results explicitly show that the performance of the proposed FLPI controller is superior to conventional PI and FLPI controllers in terms of overshoot and settling time. Furthermore, the robustness of the proposed FLPI controller under variation of system parameters and load change are higher than that of conventional PI and FLPI controllers.

• Proceedings of the KIEE Conference
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• 2004.10a
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• pp.173-175
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• 2004

This paper presents a novel design of a self tuning PI controller of induction motor using fuzzy control. In this approach, the fuzzy tuning of a PI controller gains is achieved through fuzzy rules deduced from many robustness simulation tests applied to several induction motors, for a variety of operating conditions such as response to speed command from standstill, step load torque application and speed variations, with nominal parameters and an changed rotor resistance, self inductance and inertia. Simulation results on a speed controller of induction motor are presented to show the effectiveness of the proposed gain tuner. And this controller is better than the fixed gains one in terms of robustness, even under great variations of operating conditions and load disturbance.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.1086-1088
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• 1993

A robust fuzzy self-organizing controller(SOC) is proposed for an environmental temperature chamber. Although fuzzy SOC can improve the performance of nonlinear system, the controller is ineffective to solve the performance degradation owing to the time varying factors. In this paper, we construct the fuzzy SOC with a predictive scheme based on the 386PC. The usefulness of the proposed scheme is shown through the comparison of the PI controller and the fuzzy controller.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2009.05a
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• pp.420-423
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• 2009

The conventional fixed gain PI controller is very sensitive to step change of command speed, parameter variation and load disturbances. The precise speed control of interior permanent magnet synchronous motor(IPMSM) drive becomes a complex issue due to nonlinear coupling among its winding currents and the rotor speed as well as the nonlinear electromagnetic developed torque. Therefore, there exists a need to tune the PI controller parameters on-line to ensure optimum drive performance over a wide range of operating conditions. This paper is proposed hybrid intelligent-PI(HIPI) controller of IPMSM drive using adaptive learning mechanism(ALM) and fuzzy neural network(FNN). The proposed controller is developed to ensure accurate speed control of IPMSM drive under system disturbances and estimation of speed using artificial neural network(ANN) controller. The PI controller parameters are optimized by ALM-FNN at all possible operating condition in a closed loop vector control scheme. The validity of the proposed controller is verified by results at different dynamic operating conditions.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.962-966
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• 1996

A conventional PI controller does not provide a proper response in face of various kinds of load variation. In this paper, three types of fuzzy-PI hybrid control scheme are proposed in order to improve the performance of the PI controller. The proposed control schemes are applied to the speed controller of AC servo motor systems. The effectiveness of the proposed methods is shown by computer simulation and the advantage of each control scheme is discussed.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.71-74
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• 1995

In this paper, a new PID fuzzy controller(FC) based on parallel operation of PI and PD fuzzy control is presented. First, two fuzzy rule bases are constructed by separating the linguistic control rule for PID FC into two parts : one is e-.DELTA.e part, and the other is .DELTAL.$^{2}$e-.DELTA.e part. And then two FCs employing these rule bases indivisually are synthesized and run in parallel. The incremental control input is determined by taking weighted mean of the outputs of two FCs. The proposed PID FC improves the transient response of the system and gives better performance than the conventional PI FC.